{"id":"W2113531233","doi":"10.1109/wcnc.2005.1424545","title":"Improved tomlinson-harashima precoding for the downlink of multiple antenna multi-user systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Precoding; Telecommunications link; Minimum mean square error; Minimax; Algorithm; Computer science; Control theory (sociology); Mathematics; Antenna (radio); Channel (broadcasting); Topology (electrical circuits); MIMO; Telecommunications; Estimator; Mathematical optimization; Statistics; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003295408,0.0004603248,0.000446329,0.0002288248,0.0002246392,0.0003756876,0.0003724539,0.0003325856,0.001025318],"category_scores_gemma":[0.001519826,0.0001642583,0.0002553818,0.0004865663,0.0003299495,0.0005412264,0.0003307289,0.0004562963,0.0003155389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003253037,"about_ca_system_score_gemma":0.0006896316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001513059,"about_ca_topic_score_gemma":0.003430845,"domain_scores_codex":[0.9997548,0.00009099215,0.00001027393,0.00003096593,0.00009163089,0.00002131213],"domain_scores_gemma":[0.9997709,0.00009430211,0.00002468327,0.00004115827,0.0000604658,0.000008490443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000228404,0.00004867801,0.0008118489,0.000247833,0.00006824217,0.0001843743,0.0002559258,0.573634,0.03881824,0.07953861,0.002559417,0.3036045],"study_design_scores_gemma":[0.00001677225,0.0001311695,0.0002197369,0.00001162935,0.00001540875,0.00011387,0.00002928971,0.9809127,0.006251645,0.008850574,0.003432584,0.000014542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01209183,0.0004114177,0.9857082,0.00007754795,0.00004463306,0.00001353306,0.00001832189,0.00006536235,0.001569175],"genre_scores_gemma":[0.3944556,0.001183312,0.5994512,0.0001005772,0.0001063185,0.00006043485,0.0001039194,0.0000314218,0.004507202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001513059,"threshold_uncertainty_score":0.003430009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01817384809270375,"score_gpt":0.2417523717160243,"score_spread":0.2235785236233206,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}